Trying out world map

Creating a interactive choropleth world map

library(gapminder)
library(ggplot2)
library(plotly)

Attaching package: 'plotly'

The following object is masked from 'package:ggplot2':

    last_plot

The following object is masked from 'package:stats':

    filter

The following object is masked from 'package:graphics':

    layout

library(dplyr)

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

library(ggthemes)
library(RColorBrewer)
library(crosstalk)
library(DT)

world <- map_data("world") %>%
  filter(region != "Antarctica")

Cleaning and processing of data, outputing top 5 rows

data <- read.csv("/private/test.csv")
head(data)

  X                          Country Fertility Population Test CountryCode
1 1                            Niger      6.82  24785.587  NER         NER
2 2                          Somalia     6.312  16801.170  SOM         SOM
3 3                             Chad     6.255  16910.218  TCD         TCD
4 4 Democratic Republic of the Congo     6.156  94374.379  COD         COD
5 5         Central African Republic     5.978   5414.014  CAF         CAF
6 6                             Mali     5.956  21561.299  MLI         MLI

data <- data %>%
  mutate(Fertility = as.numeric(as.character(Fertility)))

Warning: There was 1 warning in `mutate()`.
ℹ In argument: `Fertility = as.numeric(as.character(Fertility))`.
Caused by warning:
! NAs introduced by coercion

head(data)

  X                          Country Fertility Population Test CountryCode
1 1                            Niger     6.820  24785.587  NER         NER
2 2                          Somalia     6.312  16801.170  SOM         SOM
3 3                             Chad     6.255  16910.218  TCD         TCD
4 4 Democratic Republic of the Congo     6.156  94374.379  COD         COD
5 5         Central African Republic     5.978   5414.014  CAF         CAF
6 6                             Mali     5.956  21561.299  MLI         MLI

Baseline code for the Map

#| include = FALSE
#| 
# Set figure dimensions
#| fig.width=7
#| fig.height=5

# Display all Brewer palettes
display.brewer.all()

# Filter Gapminder data and join with world map data
  mapa_animado_3 <- data %>%
  right_join(world, by = c(Country = "region")) %>%
  ggplot(aes(long, lat, group = group, fill = `Fertility`)) +
  geom_polygon(color = "white", size = 0.01) +
  theme_void() +
  scale_fill_distiller(palette = "Spectral", name = "Fertility Rate") + # Use a continuous palette
  labs(title = "Population & Fertility Rate", subtitle = "year: 2022")  +
  theme(
    plot.title = element_text(size = 12, hjust = 0.5),
    plot.subtitle = element_text(size = 10, hjust = 0.5),
    plot.caption = element_text(size = 8, hjust = 1)
  ) +
  coord_fixed(ratio = 1.3)

Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.

# Convert ggplot object to a ggplotly object
fig_3 <- ggplotly(mapa_animado_3)

fig_3

Trying to add hovertext with data and data Frame

# Assuming 'world' and 'data' are already loaded and prepared
# Create a hover text column in 'data'
data$hover_text <- paste("Country: ", data$Country, "<br>Fertility Rate: ", data$Fertility, "<br>Population: ", data$Population)

joined_data <- data %>%
  right_join(world, by = c(Country = "region")) 

# Proceed with your plotting
mapa_animado_3 <- joined_data %>%
  ggplot(aes(x = long, y = lat, group = group, fill = Fertility, text = hover_text)) + # Added 'text' aesthetic for custom hover info
  geom_polygon(color = "white", size = 0.01) +
  theme_void() +
  scale_fill_distiller(palette = "Spectral", name = "Fertility Rate") + # Use a continuous palette
  labs(title = "Population & Fertility Rate", subtitle = "year: 2022")  +
  theme(
    plot.title = element_text(size = 12, hjust = 0.5),
    plot.subtitle = element_text(size = 10, hjust = 0.5),
    plot.caption = element_text(size = 8, hjust = 1)
  ) +
  coord_fixed(ratio = 1.3)

# Convert ggplot object to a ggplotly object with hoverinfo
fig_3 <- ggplotly(mapa_animado_3, tooltip = "text") # Specify 'text' to use the 'text' aesthetic for the tooltip
fig_3

displaying my joined_data into a dataframe and remove repeated country names

joined_data <- data %>%
  right_join(world, by = c(Country = "region")) %>%
    distinct(Country, .keep_all = TRUE)

datatable(joined_data, options = list(autoWidth = TRUE))

Trying out Animation element to my map

library(shiny)

Attaching package: 'shiny'

The following objects are masked from 'package:DT':

    dataTableOutput, renderDataTable

The following object is masked from 'package:crosstalk':

    getDefaultReactiveDomain

library(plotly)
library(ggplot2)
library(dplyr)


# Data preparation

# Data preparation
  data <- read.csv("/private/test.csv") # Adjust path as necessary
  data <- data %>%
    mutate(Fertility = as.numeric(as.character(Fertility)),
  hover_text = paste("Country: ", Country, "<br>Fertility Rate: ", Fertility, "<br>Population: ", Population))  # Add 'hover_text' here after 'data' is defined

Warning: There was 1 warning in `mutate()`.
ℹ In argument: `Fertility = as.numeric(as.character(Fertility))`.
Caused by warning:
! NAs introduced by coercion

# UI definition
  
  world <- map_data("world") %>%
    filter(region != "Antarctica")
  
  joined_data <- data %>%
    right_join(world, by = c(Country = "region"))
    

ui <- fluidPage(
  titlePanel("Interactive World Map and Data Table"),
  actionButton("toggle_fertility", "Countries below fertility rate "),
  plotlyOutput("worldMap")
)

server <- function(input, output, session) {
  # Reactive value to track the toggle state
  show_filtered <- reactiveVal(FALSE)
  
  # Observe the toggle button click
  observeEvent(input$toggle_fertility, {
    # Toggle the state
    current_state <- show_filtered()
    show_filtered(!current_state)
  })
  
  output$worldMap <- renderPlotly({
    # Conditional color mapping based on 'show_filtered()' state
    color_mapping <- if(show_filtered()) {
      aes(fill = ifelse(Fertility < 2.1, Fertility, NA))
    } else {
      aes(fill = Fertility)
    }
    
    mapa_animado_3 <- joined_data %>%
      ggplot(aes(x = long, y = lat, group = group, text = hover_text)) +
      geom_polygon(color = "white", size = 0.01, color_mapping) +
      scale_fill_distiller(palette = "Spectral", name = "Fertility Rate",
                           na.value = "grey", limits = range(joined_data$Fertility, na.rm = TRUE)) +
      theme_void() +
      labs(title = "Population & Fertility Rate", subtitle = "year: 2022") +
      theme(
        plot.title = element_text(size = 12, hjust = 0.5),
        plot.subtitle = element_text(size = 10, hjust = 0.5),
        plot.caption = element_text(size = 8, hjust = 1)
      ) +
      coord_fixed(ratio = 1.3)
    
    ggplotly(mapa_animado_3, tooltip = "text")
  })
}

shinyApp(ui, server)

Shiny applications not supported in static R Markdown documents